Panning for Gold: Model-X Knockoffs for High-dimensional Controlled Variable Selection

@article{Cands2016PanningFG,
  title={Panning for Gold: Model-X Knockoffs for High-dimensional Controlled Variable Selection},
  author={E. Cand{\`e}s and Yingying Fan and Lucas Janson and Jinchi Lv},
  journal={arXiv: Methodology},
  year={2016}
}
Many contemporary large-scale applications involve building interpretable models linking a large set of potential covariates to a response in a nonlinear fashion, such as when the response is binary. [...] Key Method To address such a practical problem, we propose a new framework of $model$-$X$ knockoffs, which reads from a different perspective the knockoff procedure (Barber and Cand\`es, 2015) originally designed for controlling the false discovery rate in linear models. Whereas the knockoffs procedure is…Expand
High-dimensional variable selection for ordinal outcomes with error control
RANK: Large-Scale Inference With Graphical Nonlinear Knockoffs
IPAD: Stable Interpretable Forecasting with Knockoffs Inference
Submitted to the Annals of Statistics ROBUST INFERENCE WITH KNOCKOFFS By Rina
IPAD: Stable Interpretable Forecasting with Knockoffs Inference
Kernel Knockoffs Selection for Nonparametric Additive Models
Large-scale model selection in misspecified generalized linear models
Model-free Knockoffs for SLOPE-Adaptive Variable Selection with Controlled False Discovery Rate
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 61 REFERENCES
Familywise error rate control via knockoffs
Controlling the false discovery rate via knockoffs
On Model Selection Consistency of Lasso
A SIGNIFICANCE TEST FOR THE LASSO.
Near-ideal model selection by ℓ1 minimization
SLOPE-ADAPTIVE VARIABLE SELECTION VIA CONVEX OPTIMIZATION.
Genome-wide association analysis by lasso penalized logistic regression
...
1
2
3
4
5
...